Method and device for localized blind watermark generation and detection

ABSTRACT

The present disclosure discloses a method and device for localized blind watermark generation and detection. The method for localized blind watermark generation may include: generating an N-dimensional pseudorandom initial sequence according to a preset key, and generating a 2N-dimensional sequence by inverting the initial sequence bit by bit and appending the inverted sequence to the initial sequence; and extracting the first 2N coefficients of a feature point of an image to form a coefficient sequence, and acquiring a parity of a bit of the coefficient sequence according to a parity of a corresponding bit of the 2N-dimensional sequence. With the present disclosure, redundant expansion may be performed on watermark data to increase the scale of test data with respect to the original bit data before embedding the test data into a transformation domain of the vicinity of a feature point of an image; during detection, a sequence extracted from the transformation domain of the vicinity of a certain feature point is checked bit by bit, and it is determined whether a watermark is embedded in the vicinity of the point base on the result of the examination, thereby enhancing a watermark detecting efficiency.

The present application claims benefit of priority of Chinese patentapplication No. 201110430387.0 filed on Dec. 20, 2011, under theapplicant Tencent Technology (Shenzhen) Co., Ltd. and the title “methodand device for localized blind watermark generation and detection”, thefull text of which is incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to the technology of watermark detection,and in particular to method and device for localized blind watermarkgeneration and detection.

BACKGROUND

A digital watermark is an invisible identifier embedded into image data,video data, or audio data, and can be used for copyright protection,authentication, and tracking of multi-media data, and the like.

Digital watermarking technologies may be divided into expresswatermarking and blind watermarking according to watermark extraction.Extraction of an express watermark requires original data in which thewatermark is embedded, while a blind watermark only requires a key.Generally speaking, the express watermark is robust, but cost a lot instorage, and does not meet a practical requirement very well. Therefore,the blind watermark is a trend in watermarking algorithm research.

Image watermarking technologies may be divided into a globally embeddedwatermarking and a locally embedded watermarking according to the way inwhich a watermark is embedded. The watermark information in the globallyembedded watermarking is embedded into a transformation domain of thewhole image, such as a space domain, a frequency domain, a waveletdomain, or the like. Experiments show that such a method has arelatively robust resistance against an interference such as JPEGcompression, interference by noise, filtering, or the like. However, asthe information is embedded in the whole image, when the image istailored, the size of the original image and the position of thetailored image in the original image are unavailable, it will bedifficult to determine the position where the watermark is embedded, andtherefore a globally embedded watermark is susceptible to an attack bytailoring; a locally embedded watermark is embedded based on content ofthe image, and the watermark information is repeatedly embedded onto atransformation domain of the vicinity of a relatively stable andprominent feature point in the image. Thus, even if image goes through alarge-scale tailoring or modification, the position of the watermark canstill be determined through the feature point, thereby recovering thewatermark information. As in theory, the localized watermark has a goodrobustness against various attacks, and the localized watermark hasbecome a hot spot of research in recent years.

Localized blind watermarking is a combination of both the blindwatermarking and the localized watermarking. Localized blindwatermarking in relevant art mainly relates to techniques such aswatermark embedding, watermark detecting and extracting, and the like. Aflow of embedding a localized blind watermark is as follows: first, anumber of feature points in the original image is extracted, and localDCT (Discrete Cosine Transform) or Wavelet transformation is performedon the vicinity of the feature points; then, a pseudorandom bit sequencegenerated by a specific key (namely, the watermark information) isembedded into the transformation domain according to a preset embeddingrule; finally, a local inverse transformation is performed to obtain awatermarked image. A flow of detecting and extracting a localized blindwatermark is as follows: a feature point of an image is extracted, andlocal DCT or Wavelet transformation is performed on the vicinity of thefeature point; then, a bit sequence with the same dimension as thewatermark information is extracted based on a preset extracting rule,and a match is performed to obtain a degree of similarity of the bitsequence with a pre-embedded watermark information (available from thekey); and a watermark is deemed to exist if the degree of similarity isgreater than a certain threshold T, otherwise no watermark is deemed toexist.

There are some disadvantages associated with the aforementionedlocalized blind watermarking, namely:

1) Watermark detection is still key-dependent, and during the detection,different keys are required for the match in order to complete thedetection, thus leading to a low detecting efficiency;

2) when performing the match to obtain a degree of similarity with thewatermark information, each bit in a watermark information space has, bydefault, the same credibility in the match, leading to no accurate matchin some cases, for example: assume an unknown sequence of 11111,watermark A of 11110, watermark B of 01111, in which case it isimpossible to determine which one of watermarks A and B is more crediblewhen the same extracted sequence has the same degree of similarity withthe two different watermarks A and B; according to a match based on thedifference, there is only one bit in both watermarks A and B that isdifferent from that in the unknown sequence, and it is impossible todetermine whether the unknown sequence is watermark A or watermark B,thus leading to a low detecting accuracy.

SUMMARY

According to various embodiments, the present disclosure provides amethod and device for localized blind watermark generation and detectioncapable of enhancing the efficiency and accuracy of watermark detecting.

An embodiment of the present disclosure proposes a method for localizedblind watermark generation, including:

generating an N-dimensional pseudorandom initial sequence according to apreset key, and generating a 2N-dimensional sequence by inverting theinitial sequence bit by bit and appending the inverted sequence to theinitial sequence; and

extracting the first 2N coefficients of a feature point of an image toform a coefficient sequence, and acquiring a parity of the coefficientsequence according to the parity of a corresponding bit of the2N-dimensional sequence.

An embodiment of the present disclosure further proposes a device forlocalized blind watermark generation, including:

a sequence generating unit configured to generate an N-dimensionalpseudorandom initial sequence according to a preset key, and generate a2N-dimensional sequence by inverting the initial sequence bit by bit andappending the inverted sequence to the initial sequence; and

a watermark imbedding unit configured to extract the first 2Ncoefficients of a feature point of an image to form a coefficientsequence, and acquire a parity of the coefficient sequence according tothe parity of a corresponding bit of the 2N-dimensional sequence.

An embodiment of the present disclosure further proposes a method forlocalized blind watermark detection, including:

extracting a feature point of an image, and performing domaintransformation; and

extracting a sequence of a transformation domain of the vicinity of thefeature point of the image, checking the sequence bit by bit, anddetermining that a watermark is imbedded in the vicinity of the featurepoint of the image when a number of bits with equal values in the firstN coefficients and in the last N coefficients in the sequence is withina preset range.

An embodiment of the present disclosure further proposes a device forlocalized blind watermark detection, including:

an extracting and transforming unit configured to extract a featurepoint of an image, and perform domain transformation; and

a watermark checking unit configured to extract a sequence of atransformation domain of the vicinity of the feature point of the image,check the sequence bit by bit, and determine that a watermark isimbedded in the vicinity of the feature point of the image when a numberof bits with equal values in the first N coefficients and in the last Ncoefficients in the sequence is within a preset range.

An embodiment of the present disclosure further proposes a method forlocalized blind watermark matching, including:

when a watermark is imbedded, calculating a possibility of a bit beingodd or even, and calculating a bit credibility; and

performing a watermark matching according to the bit credibility.

An embodiment of the present disclosure further proposes a device forlocalized blind watermark matching, including:

a credibility calculating unit configured to calculate a possibility ofa bit being odd or even, and calculate a bit credibility when awatermark is imbedded; and

a watermark matching unit configured to perform a watermark matchingaccording to the bit credibility.

With the method and device for localized blind watermark generation anddetection according to embodiments of the present disclosure, redundantexpansion may be performed on watermark data to increase the scale oftest data with respect to the original bit data (by at least a factor of2, for example) before embedding the test data into a transformationdomain of the vicinity of a feature point of an image; during detection,a sequence extracted from the transformation domain of the vicinity of acertain feature point is checked bit by bit, and it is determinedwhether a watermark is embedded in the vicinity of the point base on theresult of the check; as the technical solution of an embodiment of thepresent disclosure the is key-independent, the existence of a watermarkis determined directly from a feature of an image per se, therebyenhancing a watermark detecting efficiency; meanwhile, during watermarkmatching, watermark matching may be performed according to the bitcredibility; by observing the distribution of each bit in sequencesextracted at different valid points, the credibility of each bit isgiven based on posteriori estimation, and watermark matching isperformed according to the credibility, thereby enabling enhancedaccuracy in watermark identification. As a watermark is embedded by wayof localized embedding, the watermark has excellent robustness againstattacks such as image cropping, partial PS (Photoshop) processing ormodification of content of the image, or the like, thus meeting apractical requirement better.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart of steps in an embodiment of a method forlocalized blind watermark generation according to the presentdisclosure;

FIG. 2 is a flowchart of steps in an embodiment of a device forlocalized blind watermark generation according to the presentdisclosure;

FIG. 3 is a flowchart of steps in an embodiment of a method forlocalized blind watermark detection according to the present disclosure;

FIG. 4 is a flowchart of steps in another embodiment of a method forlocalized blind watermark detection according to the present disclosure;

FIG. 5 is a flowchart of steps a flowchart of steps of calculating awatermark credibility in an embodiment of a method for localized blindwatermark detection according to the present disclosure;

FIG. 6 is a schematic diagram of a structure in an embodiment of adevice for localized blind watermark detection according to the presentdisclosure;

FIG. 7 is a schematic diagram of a structure in another embodiment of adevice for localized blind watermark detection according to the presentdisclosure;

FIG. 8 is a flowchart of steps in an embodiment of another method forlocalized blind watermark matching according to the present disclosure;

FIG. 9 is a flowchart of steps of calculating a watermark credibility inan embodiment of another method for localized blind watermark matchingaccording to the present disclosure; and

FIG. 10 is a schematic diagram of a structure in an embodiment ofanother device for localized blind watermark matching according to thepresent disclosure.

DETAILED DESCRIPTION

It should be noted that specific embodiments described here is merelyintended to explain the present disclosure, and is not intended to limitthe present disclosure.

FIG. 1 illustrates an embodiment of a method for generating a localizedblind watermark according to the present disclosure. The method mayinclude:

Step S60, generating an N-dimensional pseudorandom initial sequenceaccording to a preset key, and generating a 2N-dimensional sequence byinverting the initial sequence bit by bit and appending the invertedsequence to the initial sequence; and

Step S61, extracting the first 2N coefficients of a feature point of animage to form a coefficient sequence, and acquiring a parity of thecoefficient sequence according to the parity of a corresponding bit ofthe 2N-dimensional sequence.

Step S61 may specifically include: extracting the first 2N coefficientsof a DCT block in the feature point of the image, obtaining thecoefficient sequence by arranging the extracted coefficients in onedimension, quantizing the coefficient sequence, acquiring the parity ofeach quantized bit of coefficient of the coefficient sequence accordingto the parity of a bit of the 2N-dimensional sequence corresponding tothe quantized bit of coefficient of the 2N coefficient sequence. Thepreset key may be an original image file (data), the initial sequence isa sequence generated by performing an MD5 algorithm on the originalimage file.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, and performing watermark embedding.

The procedure for generating watermark information may be: generating anN-dimensional pseudorandom initial sequence S according to a specifickey K, and generating a 2N-dimensional sequence SS by inverting theinitial sequence S bit by bit and appending the inverted sequence to theinitial sequence S. In this embodiment, the key K may be the originalimage file, sequence S may be a 128-dimensional sequence generated byperforming an MD5 algorithm on the original image file.

The procedure for extracting a feature point of an image may be: anRGB→YCrCb color domain transformation is performed on the originalimage, an illumination component Y in YCrCb is extracted. A Harrisangular point is extracted on a Y diagram; and to avoid interferenceamong pieces of embedded watermark information, it is required thatthere is at least a certain distance D between spatial positions ofextracted angular points. In the embodiment, D may take a value of 48pixels, a Harris window may have a size of 5×5 pixels.

The DCT transformation may be: performing a sub-block DCT transformationin an R×R-pixel window of the vicinity of each extracted feature point,with a block size of 8×8. In this embodiment, R may take a value of 32.

The performing watermark embedding may be that: for each OCT-transformedfeature point, the first M coefficients of all DCT blocks are extractedin a zig-zag way, and a coefficient sequence W is obtained by arrangingthe extracted coefficients in one dimension, wherein the dimension of Wis to be kept equal to that of the watermark sequence SS. Thenquantization is performed with a quantizing factor of F, and the parityof each quantized coefficient of the coefficient sequence W isdetermined depending on whether a bit in the sequence SS has a value of0 or 1. In the embodiment, M may take a value of 16, and when SS[i] is0, W[i] takes an even number closest to W[i] after the quantization,otherwise W[i] takes an odd number.

With the method for localized blind watermark generation, duringwatermark detection, a sequence extracted from a transformation domainof the vicinity of a certain feature point under detection may bechecked bit by bit, and it is determined whether a watermark is embeddedin the vicinity of the point base on the result of the check. Thus,watermark detection is no longer key-dependent, which enables a fasterand easier watermark detection with a better detection efficiency.

Referring to FIG. 2, the present disclosure introduces an embodiment ofa device for localized blind watermark generation. The device mayinclude a sequence generating unit 71 and a watermark imbedding unit 72.The sequence generating unit 71 is configured to generate anN-dimensional pseudorandom initial sequence according to a preset key,and generate a 2N-dimensional sequence by inverting the initial sequencebit by bit and appending the inverted sequence to the initial sequence;the watermark imbedding unit 72 is configured to extract the first 2Ncoefficients of a feature point of an image to form a coefficientsequence, and acquire a parity of the coefficient sequence according tothe parity of a corresponding bit of the 2N-dimensional sequence.

The watermark imbedding unit 72 is specifically configured to: extractthe first 2N coefficients of a DCT block in the feature point of theimage, obtain the coefficient sequence by arranging the extractedcoefficients in one dimension, quantize the coefficient sequence,acquire the parity of each quantized coefficient of the coefficientsequence according to the parity of a bit of the 2N-dimensional sequencecorresponding to the 2N coefficient sequence. The preset key may be anoriginal image file (data), the initial sequence is a sequence generatedby performing an MD5 algorithm on the original image file.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, and performing watermark embedding,wherein the generating watermark information is executed by the sequencegenerating unit 71, and the rest of the flow of embedding a watermark inan image is executed by the watermark imbedding unit 72.

The generating watermark information may be: generating an N-dimensionalpseudorandom initial sequence S according to a specific key K, andgenerating a 2N-dimensional sequence SS by inverting the initialsequence S bit by bit and appending the inverted sequence to the initialsequence S. In the embodiment, key K may be the original image file,sequence S may be a 128-dimensional sequence generated by performing anMD5 algorithm on the original image file.

The extracting a feature point of an image may be that: an RGB→YCrCbcolor domain transformation is performed on the original image, anillumination component Y in YCrCb is extracted. a Harris angular pointis extracted on a Y diagram, to avoid interference among pieces ofembedded watermark information, it is required that there is at least acertain distance D between spatial positions of extracted angularpoints. In the embodiment, D may take a value of 48 pixels, a Harriswindow may have a size of 5×5 pixels.

The DCT transformation may be: performing a sub-block DCT transformationin an R×R-pixel window of the vicinity of each extracted feature point,with a block size of 8×8. In the embodiment, R may take a value of 32.

The performing watermark embedding may be that: for each OCT-transformedfeature point, the first M coefficients of all DCT blocks are extractedin a zig-zag way, and a coefficient sequence W is obtained by arrangingthe extracted coefficients in one dimension, wherein the dimension of Wis to be kept equal to that of the watermark sequence SS. Thenquantization is performed with a quantizing factor of F, and the parityof each quantized coefficient of the coefficient sequence W isdetermined depending on whether a bit in the sequence SS has a value of0 or 1. In the embodiment, M may take a value of 16, and when SS[i] is0, W[i] takes an even number closest to W[i] after the quantization,otherwise W[i] takes an odd number.

With the aforementioned device for localized blind watermark generation,during watermark detection, a sequence extracted from a transformationdomain of the vicinity of a certain feature point under detection may bechecked bit by bit, and it is determined whether a watermark is embeddedin the vicinity of the point based on the result of the check. Thus,watermark detection is no longer key-dependent, which enables a fasterand easier watermark detection with a better detection efficiency.

Referring to FIG. 3, an embodiment of a method for localized blindwatermark detection according to the present disclosure is introduced.The method may include:

step S10, extracting a feature point of an image, and performing domaintransformation; and

step S11, extracting a sequence of a transformation domain of thevicinity of the feature point of the image, checking the sequence bit bybit, and determining that a watermark is imbedded in the vicinity of thefeature point of the image when a number of bits with equal values inthe first N coefficients and in the last N coefficients in the sequenceis within a preset range.

With the method for localized blind watermark detection, duringwatermark detection, a sequence extracted from a transformation domainof the vicinity of a certain feature point under detection may bechecked bit by bit, and it is determined whether a watermark is embeddedin the vicinity of the point base on the result of the check. Thus,watermark detection is no longer key-dependent, which enables a fasterand easier watermark detection with a better detection efficiency.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, performing watermark embedding, andacquiring a watermarked image.

The generating watermark information may be: generating an N-dimensionalpseudorandom initial sequence S according to a specific key K, andgenerating a 2N-dimensional sequence SS by inverting the initialsequence S bit by bit and appending the inverted sequence to the initialsequence S. In the embodiment, the key K may be the original image file,and the sequence S may be a 128-dimensional sequence generated byperforming an MD5 algorithm on the original image file.

The extracting a feature point of an image may be that: an RGB→YCrCbcolor domain transformation is performed on the original image, anillumination component Y in YCrCb is extracted. A Harris angular pointis extracted on a Y diagram; and to avoid interference among pieces ofembedded watermark information, it is required that there is at least acertain distance D between spatial positions of extracted angularpoints. In the embodiment, D may take a value of 48 pixels, and a Harriswindow may have a size of 5×5 pixels.

The DCT transformation may be: performing a sub-block DCT transformationin an R×R-pixel window of the vicinity of each extracted feature point,with a block size of 8×8. In the embodiment, R may take a value of 32.

The performing watermark embedding may be that: for each OCT-transformedfeature point, the first M coefficients of all DCT blocks are extractedin a zig-zag way, and a coefficient sequence W is obtained by arrangingthe extracted coefficients in one dimension, wherein the dimension of Wis to be kept equal to that of the watermark sequence SS. Thenquantization is performed with a quantizing factor of F, and the parityof each quantized coefficient of the coefficient sequence W isdetermined depending on whether a bit in the sequence SS has a value of0 or 1. In the embodiment, M may take a value of 16, and when SS[i] is0, W[i] takes an even number closest to W[i] after the quantization,otherwise W[i] takes an odd number.

The flow of acquiring a watermarked image may be: performing inversetransformation on all DCT blocks and obtaining a new Y1 component, thenperforming the YCrCb→RGB transformation and obtaining the watermarkedRGB image.

In image watermark detection, the method may include: extracting afeature point of an image, performing DCT transformation, detectingwhether there is any watermark, calculating a watermark credibility,watermark identifying and matching, and the like.

The processing flow in the extracting a feature point of an image andthe performing DCT transformation in the step S10 may be the same as theprocessing flow in the extracting a feature point of an image and theperforming DCT transformation during the watermark embedding.

The step S11 is the processing flow of the detecting whether there isany watermark, which may specifically include: extracting a coefficientsequence made up of multiple coefficients of a sub-block DCT of thevicinity of the feature point of the image, counting the number of bitswith equal values in the first N coefficients and in the last Ncoefficients in the coefficient sequence, and determining that awatermark is imbedded in the vicinity of the feature point of the imagewhen the number is less than a preset threshold (or greater than apreset threshold), wherein the value of a bit is calculated according tothe parity of the bit, and the N is a positive integer.

During detection, for each feature point P of the image, a coefficientsequence W made up of the first M coefficients of the sub-block DCT ofthe vicinity of the feature point is extracted, and the parity of eachcoefficient W[i] is tested, wherein i is a natural number. In theembodiment, if W[i] is odd, then the detected sequence UnKnowSS[i] takesa bit value of 1, otherwise UnKnowSS[i] takes a bit value of 0. A numberQ of bits with equal values in the first N coefficients (i.e. fromUnKnowSS[0] to UnKnowSS[i]) and in the last N coefficients (i.e. fromUnKnowSS[i+1] to UnKnowSS[i+N]) in the UnKnowSS is counted; and if Q isless than a preset threshold T, then the feature point is deemed to be avalid point, in which case the sequence UnknownSS is a valid sequenceValidSS, namely, includes valid watermark information. In theembodiment, the T may take a value of 12.

Referring to FIG. 4, after step S11, the method in another embodiment ofthe present disclosure may include:

step S111, calculating a possibility of a bit being odd or even, andcalculating a bit credibility when a watermark is imbedded; and

step S112, performing a watermark matching according to the bitcredibility.

Referring to FIG. 5, the step S111 may be the processing flow ofcalculating a watermark credibility, which may specifically include:

step S1111, when a watermark is imbedded, counting a count Zero[i] of aneven ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculating a possibility of a bit beingodd based on a formula: oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1),and calculating a possibility of a bit being even based on a formula:zeroProb[i]=ε^((2V−zero[1])) (1−ε)^(zero[i]) (2), wherein ε is anaverage error rate on each bit, and i is a natural number;

step S1112, when there is a greater possibility of a bit being odd,calculating the credibility as oneProb[i]/(oneProb[i]+zeroProb[i]); and

step S1113, when there is a greater possibility of a bit being even,calculating the credibility as zeroProb[i]/(oneProb[i]+zeroProb[i]).

Assume a number of valid points of V, arrays Zero[i], oneProb[i],zeroProb[i] are applied, with i being natural numbers 0, 1, 2, . . . . Acount of the ith bit being 0 and the (i+N)th bit being 1 in each ofsequences ValidSS generated by all valid points is counted. Namely, foreach sequence ValidSS, if ValidSS[i]=0 and ValidSS[i+N]=1, then Zero[i]increases by 1. Then, the possibility of each bit being 0 or 1 iscalculated based on formulae (1) or (2):oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1);zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2). Wherein, oneProb[i]and zeroProb[i] are relatively possibilities of each bit being 0 or 1. εis an average error rate on each bit that is available through counting.Assume that a watermark sequence SS[i] is output, ifoneProb[i]>zeroProb[i], then SS[i]=1 is output, with the possiblecredibility being oneProb[i]/(oneProb[i]+zeroProb[i]), otherwise SS[i]=0is output, with the credibility beingzeroProb[i]/(oneProb[i]+zeroProb[i]).

Step S112 may be the processing flow of watermark identifying andmatching, which may specifically include: comparing the sequence withmassive watermark information in a database according to a descendingcredibility, and when an error occurs to the ith bit during thecomparison, returning to a resulted watermark that matches thecoefficient sequence on those bits from the 0th bit to the (i−1)th bit.

The specific reasoning process in step S11 is as follows.

Assume that a category WATERMARK is w1, a category NON-WATERMARK is w2,and a state of a count Q of bits with equal values in the first Ncoefficients (from UnKnowSS[0] to UnKnowSS[i]) and in the last Ncoefficients (from UnKnowSS[i+1] to UnKnowSS[i+N]) in the unknownsequence UnKnowSS is θ, then the possibility of determining that thestate belongs to the category WATERMARK is p(q1|θ), and the possibilityof determining that the state belongs to the category NON-WATERMARK isp( w2|θ), and according to a Bayesian posteriori estimation:

$\begin{matrix}{{{p\left( {{w\; 1}\theta} \right)} = \frac{{p\left( {\theta {w\; 1}} \right)}{p\left( {w\; 1} \right)}}{{{p\left( {\theta {w\; 1}} \right)}{p\left( {w\; 1} \right)}} + {{p\left( {\theta {w\; 2}} \right)}{p\left( {w\; 2} \right)}}}};} & (3)\end{matrix}$

Assume that the possibilities of an equal bit for any match of sequenceUnKnowSS <UnKnowSS[i],UnKnowSS[i+N]> in case of category WATERMARK w1are independent of each other, and are all P(BitAccord|w1) then:

p(θ|w1)=C _(N) ^(Q) P(BitAccord|w1)^(Q) P(BitDisAccord|w1)^((N−Q))  (4);

likewise:

p(θ|w2)=C _(N) ^(Q) P(BitAccord|w2)^(Q) P(BitDisAccord|w2)^((N−Q))  (5);

In case of category WATERMARK w1, the average error rate of change ofeach bit due to noise and compression is ε, then:

P(BitAccord|w1)=2ε(1−ε)   (6);

In case of category NON-WATERMARK w2:

P(BitAccord|w2)=P (BitDisAccord|w2)=0.5   (7);

Let R=p(w2)/p(w1), then putting formulae (4)-(7) into formula (3)results in

$\begin{matrix}{{{p\left( {{w\; 1}\theta} \right)} = \frac{(0.19)^{12}(0.81)^{116}2^{128}}{{(0.19)^{12}(0.81)^{116}2^{128}} + R}};} & (8)\end{matrix}$

Experiments and statistics give that under tailoring, formattransformation, and mild compression (with a compression rate no lessthan 60%), estimated ε is lower than 0.1, putting the estimation intoformula (8), and letting N=128, Q=12,R<10000 results in

$\begin{matrix}{{{p\left( {{w\; 1}\theta} \right)} = {\frac{(0.19)^{12}(0.81)^{116}2^{128}}{{(0.19)^{12}(0.81)^{116}2^{128}} + R} > {1 - (0.1)^{15}}}};} & (9)\end{matrix}$

It may be known from the derivation that when Q<=12, it's possible todetermined that unknown sequence UnKnowSS belongs to the categoryWATERMARK.

The specific reasoning process of the step S111 is as follows.

Assume that the real watermark informaiton corresponding to a validsequence ValidSS is SS, then on each bit:

p(ValidSS[i]=1|SS[i]=0)=p(ValidSS[i]=0|SS[i]=1)=ε  (10);

Assuming a number of valid points V, a state sequence Bit[i][j] isformed with sequences ValidSS generated by all valid points, whereini=0,1, . . . , 2*N; j=0,1, . . . , V; then according to a Bayesianposteriori formula:

$\begin{matrix}{{{p\left( {{{SS}\lbrack i\rbrack} = {0{{Bit}\lbrack i\rbrack}}} \right)} = \frac{{p\left( {{{{Bit}\lbrack i\rbrack}{{SS}\lbrack i\rbrack}} = 0} \right)}{p\left( {{{SS}\lbrack i\rbrack} = 0} \right)}}{\begin{matrix}{{{p\left( {{{{Bit}\lbrack i\rbrack}{{SS}\lbrack i\rbrack}} = 0} \right)}{p\left( {{{SS}\lbrack i\rbrack} = 0} \right)}} +} \\{{p\left( {{{{Bit}\lbrack i\rbrack}{{SS}\lbrack i\rbrack}} = 1} \right)}{p\left( {{{SS}\lbrack i\rbrack} = 1} \right)}}\end{matrix}}};} & (11)\end{matrix}$

The sequence Bit[i] reflects the states of the ith and the (i+N)th bit(test bit) on different valid points, array Zero[i] indicates a numberof a 0 state on Bit[i] and a number of a 1 state on Bit[i+N]. Assumethat bit states on different points are independent of each other, thenaccording to formula (10):

p(Bit[i]|SS[i]=1)=C _(2V) ^(zero[i])ε^(zero[i])(1−ε)^(2V−zero[i])  (12);

p(Bit[i]|SS[i]=0)=C _(2V) ^(zero[i])ε^(2V−zero[i])(1−ε)^(zero[i])  (13);

Let p(SS[i]=0)=p(SS[i]=1),oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]()1),zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2), then according toformulae (12) (13), formula (11) may be rewritten as:

${{p\left( {{{SS}\lbrack i\rbrack} = {0{{Bit}\lbrack i\rbrack}}} \right)} = \frac{{zeroProb}\lbrack i\rbrack}{{{zeroProb}\lbrack i\rbrack} + {{oneProb}\lbrack i\rbrack}}},$

and likewise,

${p\left( {{{SS}\lbrack i\rbrack} = {1{{Bit}\lbrack i\rbrack}}} \right)} = {\frac{{oneProb}\lbrack i\rbrack}{{{zeroProb}\lbrack i\rbrack} + {{oneProb}\lbrack i\rbrack}}.}$

In the embodiment, with the method for localized blind watermarkdetection, redundant expansion may be performed on watermark data toincrease the scale of test data with respect to the original bit data(by at least a factor of 2, for example) before embedding the test datainto a transformation domain of the vicinity of a feature point of animage; during detection, a sequence extracted from the transformationdomain of the vicinity of a certain feature point is checked bit by bit,and it is determined whether a watermark is embedded in the vicinity ofthe point base on the result of the check, thereby enhancing a watermarkdetecting efficiency; meanwhile, during watermark matching, watermarkmatching may be performed according to the bit credibility; by observingthe distribution of each bit in sequences extracted at different validpoints, the credibility of each bit is given based on posterioriestimation, and watermark matching is performed according to thecredibility, thereby enabling enhanced accuracy in watermarkidentification. As a watermark is embedded by way of localizedembedding, the watermark has excellent robustness against attacks suchas image cropping, partial PS (Photoshop) processing or modification ofcontent of the image, or the like, thus meeting a practical requirementbetter.

Referring to FIG. 6, an embodiment of a device 20 for localized blindwatermark detection according to the present disclosure is proposed. Thedevice 20 may include an extracting and transforming unit 21 and awatermark checking unit 22. The extracting and transforming unit 21 isconfigured to extract a feature point of an image, and perform domaintransformation; and the watermark checking unit 22 is configured toextract a sequence of a transformation domain of the vicinity of thefeature point of the image, check the sequence bit by bit, and determinethat a watermark is imbedded in the vicinity of the feature point of theimage when a number of bits with equal values in the first Ncoefficients and in the last N coefficients in the sequence is within apreset range.

With the device 20 for localized blind watermark detection, duringwatermark detection, a sequence extracted from a transformation domainof the vicinity of a certain feature point under detection may bechecked bit by bit through the watermark checking unit 22, and it isdetermined whether a watermark is embedded in the vicinity of the pointbase on the result of the check. Thus, watermark detection is no longerkey-dependent, which enables a faster and easier watermark detectionwith a better detection efficiency.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, performing watermark embedding, andacquiring a watermarked image.

The generating watermark information may be: generating an N-dimensionalpseudorandom initial sequence S according to a specific key K, andgenerating a 2N-dimensional sequence SS by inverting the initialsequence S bit by bit and appending the inverted sequence to the initialsequence S. In the embodiment, the key K may be the original image file,the sequence S may be a 128-dimensional sequence generated by performingan MD5 algorithm on the original image file.

The extracting a feature point of an image may be that: an RGB→YCrCbcolor domain transformation is performed on the original image, anillumination component Y in YCrCb is extracted. A Harris angular pointis extracted on a Y diagram; and to avoid interference among pieces ofembedded watermark information, it is required that there is at least acertain distance D between spatial positions of extracted angularpoints. In the embodiment, D may take a value of 48 pixels, a Harriswindow may have a size of 5×5 pixels.

The DCT transformation may be: performing a sub-block DCT transformationin an R×R-pixel window of the vicinity of each extracted feature point,with a block size of 8×8. In the embodiment, R may take a value of 32.

The performing watermark embedding may be that: for each OCT-transformedfeature point, the first M coefficients of all DCT blocks are extractedin a zig-zag way, and a coefficient sequence W is obtained by arrangingthe extracted coefficients in one dimension, wherein the dimension of Wis to be kept equal to that of the watermark sequence SS. Thenquantization is performed with a quantizing factor of F, and the parityof each quantized coefficient of the coefficient sequence W isdetermined depending on whether a bit in the sequence SS has a value of0 or 1. In the embodiment, M may take a value of 16, and when SS[i] is0, W[i] takes an even number closest to W[i] after the quantization,otherwise W[i] takes an odd number.

The flow of acquiring a watermarked image may be: performing inversetransformation on all DCT blocks and obtaining a new Y1 component, thenperforming the YCrCb→RGB transformation and obtaining the watermarkedRGB image.

In image watermark detection, the method may include: extracting afeature point of an image, performing DCT transformation, detectingwhether there is any watermark, calculating a watermark credibility,watermark identifying and matching, and the like.

The processing flow of the extracting a feature point of an image andthe performing DCT transformation during the watermark detection may bethe same as the processing flow in the extracting a feature point of animage and the performing DCT transformation during the watermarkembedding.

The detecting whether there is any watermark may be implemented usingthe watermark checking unit 22, which may be specifically configured to:extract a coefficient sequence made up of multiple coefficients of asub-block DCT of the vicinity of the feature point of the image, countthe number of bits with equal values in the first N coefficients and inthe last N coefficients in the coefficient sequence, and determine thata watermark is imbedded in the vicinity of the feature point of theimage when the number is less than a preset threshold (or greater than apreset threshold), wherein the value of a bit is calculated according tothe parity of the bit, and the N is a positive integer.

During detection, for each feature point P of the image, a coefficientsequence W made up of the first M coefficients of the sub-block DCT ofthe vicinity of the feature point is extracted, and the parity of eachcoefficient W[i] is tested, wherein i is a natural number. In theembodiment, if W[i] is odd, then the detected sequence UnKnowSS[i] takesa bit value of 1, otherwise UnKnowSS[i] takes a bit value of 0. A numberQ of bits with equal values in the first N coefficients (i.e. fromUnKnowSS[0] to UnKnowSS[i]) and in the last N coefficients (i.e. fromUnKnowSS[i+1] to UnKnowSS[i+N]) in the UnKnowSS is counted; and if Q isless than a preset threshold T, then the feature point is deemed to be avalid point, in which case the sequence UnknownSS is a valid sequenceValidSS, namely, includes valid watermark information. In theembodiment, the T may take a value of 12.

Referring to FIG. 7, in another embodiment of the present disclosure,the device 20 further includes a credibility calculating unit 24 and awatermark matching unit 25. The credibility calculating unit 24 isconfigured to calculate a possibility of a bit being odd or even, andcalculate a bit credibility when a watermark is imbedded; and thewatermark matching unit 25 is configured to perform a watermark matchingaccording to the bit credibility.

The credibility calculating unit 24 is specifically configured to: whena watermark is imbedded, count a count Zero[i] of an even ith bit and anodd (i+N)th bit in the coefficient sequence corresponding to thewatermark, calculate a possibility of a bit being odd based on aformula: oneProb[i]=(1−ε)^((2V-zero[1]))ε^(zero[i]) (1), and calculate apossibility of a bit being even based on a formula:zeroProb[1]=ε^((2V−zero[i]) (1−ε)^(zero[i]) (2), wherein ε is an averageerror rate on each bit, i is a natural number; when there is a greaterpossibility of a bit being odd, calculate the credibility asoneProb[i]/(oneProb[i]+zeroProb[i]); and when there is a greaterpossibility of a bit being even, calculate the credibility aszeroProb[i]/(oneProb[i]+zeroProb[i]).

Assume a number of valid points of V, arrays Zero[i], oneProb[i],zeroProb[i] are applied, with i being natural numbers 0, 1, 2, . . . . Acount of the ith bit being 0 and the (i+N)th bit being 1 in each ofsequences ValidSS generated by all valid points is counted. Namely, foreach sequence ValidSS, if ValidSS[i]=0 and ValidSS[i+N]=1, then Zero[i]increases by 1. Then, the possibility of each bit being 0 or 1 iscalculated based on formulae (1) or (2):oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1);zeroProb[i]=ε^((2V−zero[) i]) (1−ε)^(zero[i]) (2). Wherein, oneProb[i]and zeroProb[i] are relatively possibilities of each bit being 0 or 1. εis an average error rate on each bit that is available through counting.Assume that a watermark sequence SS[i] is output, ifoneProb[i]>zeroProb[i], then SS[i]=1 is output, with the possiblecredibility being oneProb[i]/(oneProb[i]+zeroProb[i]), otherwise SS[i]=0is output, with the credibility beingzeroProb[i]/(oneProb[i]+zeroProb[i]).

The watermark matching unit 25 is specifically configured to: comparethe coefficient sequence with massive watermark information in adatabase according to a descending credibility, and when an error occursto the ith bit during the comparison, return to a resulted watermarkthat matches the coefficient sequence on those bits from the 0th bit tothe (i−1)th bit.

In the embodiment, with the device 20 for localized blind watermarkdetection, redundant expansion may be performed on watermark data toincrease the scale of test data with respect to the original bit data(by at least a factor of 2, for example) before embedding the test datainto a transformation domain of the vicinity of a feature point of animage; during detection, a sequence extracted from the transformationdomain of the vicinity of a certain feature point is checked bit by bit,and it is determined whether a watermark is embedded in the vicinity ofthe point base on the result of the examination, thereby enhancing awatermark detecting efficiency; meanwhile, during watermark matching,watermark matching may be performed according to the bit credibility; byobserving the distribution of each bit in sequences extracted atdifferent valid points, the credibility of each bit is given based onposteriori estimation, and watermark matching is performed according tothe credibility, thereby enabling enhanced accuracy in watermarkidentification. As a watermark is embedded by way of localizedembedding, the watermark has excellent robustness against attacks suchas image cropping, partial PS (Photoshop) processing or modification ofcontent of the image, or the like, thus meeting a practical requirementbetter.

Referring to FIG. 8, an embodiment of a method for localized blindwatermark matching according to the present disclosure is proposed. Themethod may include:

step S30, when a watermark is imbedded, calculating a possibility of abit being odd or even, and calculating a bit credibility; and

step S31, performing a watermark matching according to the bitcredibility.

Referring to FIG. 9, the step S30 may be the processing flow ofcalculating a watermark credibility, which may specifically include:

step S301, when a watermark is imbedded, counting a count Zero[i] of aneven ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculating a possibility of a bit beingodd based on a formula: oneProb[i]=(1−ε)^((2V−zero[1]))ε^(zero[i]) (1),and calculating a possibility of a bit being even based on a formula:zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2), wherein ε is anaverage error rate on each bit, and i is a natural number;

step S302, when there is a greater possibility of a bit being odd,calculating the credibility as oneProb[i]/(oneProb[i]+zeroProb[i]); and

step S313, when there is a greater possibility of a bit being even,calculating the credibility as zeroProb[i]/(oneProb[i]+zeroProb[i]).

Assume a number of valid points of V, arrays Zero[i], oneProb[i],zeroProb[i] are applied, with i being natural numbers 0, 1, 2, . . . . Acount of the ith bit being 0 and the (i+N)th bit being 1 in each ofsequences ValidSS generated by all valid points is counted. Namely, foreach sequence ValidSS, if ValidSS[i]=0 and ValidSS[i+N]=1, then Zero[i]increases by 1. Then, the possibility of each bit being 0 or 1 iscalculated based on formulae (1) or (2):oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1);zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2). Wherein, oneProb[i]and zeroProb[i] are relatively possibilities of each bit being 0 or 1. εis an average error rate on each bit that is available through counting.Assume that a watermark sequence SS[i] is output, ifoneProb[i]>zeroProb[i], then SS[i]=1 is output, with the possiblecredibility being oneProb[i]/(oneProb[i]+zeroProb[i]), otherwise SS[i]=0is output, with the credibility beingzeroProb[i]/(oneProb[i]+zeroProb[i]).

Step S31 may be the processing flow of watermark identifying andmatching, which may specifically include: comparing the sequence withmassive watermark information in a database according to a descendingcredibility, and when an error occurs to the ith bit during thecomparison, returning to a resulted watermark that matches thecoefficient sequence on those bits from the 0th bit to the (i−1)th bit.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, performing watermark embedding, andacquiring a watermarked image.

In the embodiment, with the method for localized blind watermarkmatching, redundant expansion may be performed on watermark data toincrease the scale of test data with respect to the original bit data(by at least a factor of 2, for example) before embedding the test datainto a transformation domain of the vicinity of a feature point of animage; during watermark matching, watermark matching may be performedaccording to the bit credibility; by observing the distribution of eachbit in sequences extracted at different valid points, the credibility ofeach bit is given based on posteriori estimation, and watermark matchingis performed according to the credibility, thereby enabling enhancedaccuracy in watermark identification. As a watermark is embedded by wayof localized embedding, the watermark has excellent robustness againstattacks such as image cropping, partial PS (Photoshop) processing ormodification of content of the image, or the like, thus meeting apractical requirement better.

Referring to FIG. 10, an embodiment of a device for localized blindwatermark matching according to the present disclosure is proposed. Thedevice 40 may include a credibility calculating unit 41 and a watermarkmatching unit 42. The credibility calculating unit 41 is configured tocalculate a possibility of a bit being odd or even, and calculate a bitcredibility when a watermark is imbedded; and the watermark matchingunit 42 is configured to perform a watermark matching according to thebit credibility.

The calculating a watermark credibility may be implemented specificallyusing the credibility calculating unit 41, which may be specificallyconfigured to: when a watermark is imbedded, count a count Zero[i] of aneven ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculate a possibility of a bit beingodd based on a formula: oneProb[i]=(1−ε)^((2V−zero[1])) ε^(zero[i]) (1),and calculate a possibility of a bit being even based on a formula:zeroProb[i]=ε^((2V−zero[1])) (1−ε)^(zero[i]) (2), wherein ε is anaverage error rate on each bit, i is a natural number; when there is agreater possibility of a bit being odd, calculate the credibility asoneProb[i]/(oneProb[i]+zeroProb[i]); and when there is a greaterpossibility of a bit being even, calculate the credibility aszeroProb[i]/(oneProb[i]+zeroProb[i]).

Assume a number of valid points of V, arrays Zero[i], oneProb[i],zeroProb[i] are applied, with i being natural numbers 0, 1, 2, . . . . Acount of the ith bit being 0 and the (i+N)th bit being 1 in each ofsequences ValidSS generated by all valid points is counted. Namely, foreach sequence ValidSS, if ValidSS[i]=0 and ValidSS[i+N]=1, then Zero[i]increases by 1. Then, the possibility of each bit being 0 or 1 iscalculated based on formulae (1) or (2):oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1);zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2). Wherein, oneProb[i]and zeroProb[i] are relatively possibilities of each bit being 0 or 1. εis an average error rate on each bit that is available through counting.Assume that a watermark sequence SS[i] is output, ifoneProb[i]>zeroProb[i], then SS[i]=1 is output, with the possiblecredibility being oneProb[i]/(oneProb[i]+zeroProb[i]), otherwise SS[i]=0is output, with the credibility beingzeroProb[i]/(oneProb[i]+zeroProb[i]).

The watermark identifying and matching may be implemented specificallyusing the watermark matching unit 42, which is specifically configuredto: compare the coefficient sequence with massive watermark informationin a database according to a descending credibility, and when an erroroccurs to the ith bit during the comparison, return to a resultedwatermark that matches the coefficient sequence on those bits from the0th bit to the (i−1)th bit.

The flow of embedding a watermark in an image may include: generatingwatermark information, extracting a feature point of an image,performing DCT transformation, performing watermark embedding, andacquiring a watermarked image.

In the embodiment, with the device 40 for localized blind watermarkmatching, redundant expansion may be performed on watermark data toincrease the scale of test data with respect to the original bit data(by at least a factor of 2, for example) before embedding the test datainto a transformation domain of the vicinity of a feature point of animage; during watermark matching, watermark matching may be performedaccording to the bit credibility; by observing the distribution of eachbit in sequences extracted at different valid points, the credibility ofeach bit is given based on posteriori estimation, and watermark matchingis performed according to the credibility, thereby enabling enhancedaccuracy in watermark identification. As a watermark is embedded by wayof localized embedding, the watermark has excellent robustness againstattacks such as image cropping, partial PS (Photoshop) processing ormodification of content of the image, or the like, thus meeting apractical requirement better.

Those ordinarily skilled in the art would appreciate that the abovementioned steps or units may be implemented by one or more processorswith computer program running thereon. The computer program can bestored in a non-transitory computer-readable storage medium. When thecomputer program is executed, the above steps or units can be included.

When implemented in form of a software functional module and sold orused as an independent product, an integrated module of an embodiment ofthe present disclosure may also be stored in computer-readable storagemedium. Based on such an understanding, the essential part or a partcontributing to prior art of the technical solution of an embodiment ofthe present disclosure may appear in form of a software product, whichsoftware product is stored in storage media, and includes a number ofinstructions for causing a computer (such as a personal computer, aserver, a network equipment, or the like) to execute all or part of themethods in various embodiments of the present disclosure. The storagemedium include various types of medium that can store program codes suchas a U disk, a mobile hard disk, a Read-Only Memory (ROM), a RandomAccess Memory (RAM), a magnetic disk, a CD, and the like. Thus, anembodiment of the present disclosure is not limited to any specificcombination of hardware and software.

What described are merely preferred embodiments of the presentdisclosure, and do not limit the patent scope of the present disclosure;any equivalent structure or equivalent flow variation made using thecontent of the specification and drawings of the present disclosure, orany direct/indirect application to another relevant art likewise fallsin the protection scope of the present disclosure.

1. (canceled)
 2. (canceled)
 3. (canceled)
 4. (canceled)
 5. (canceled) 6.(canceled)
 7. A method for localized blind watermark detection,comprising: extracting a feature point of an image, and performingdomain transformation; and extracting a sequence of a transformationdomain of the vicinity of the feature point of the image, checking thesequence bit by bit, and determining that a watermark is imbedded in thevicinity of the feature point of the image when a number of bits withequal values in the first N coefficients and in the last N coefficientsin the sequence is within a preset range.
 8. The method according toclaim 7, wherein the step of extracting a sequence of a transformationdomain of the vicinity of the feature point of the image, checking thesequence bit by bit, and determining that a watermark is imbedded in thevicinity of the feature point of the image when a number of bits withequal values in the first N coefficients and in the last N coefficientsin the sequence is within a preset range is: extracting a coefficientsequence made up of multiple coefficients of a sub-block DCT of thevicinity of the feature point of the image, counting the number of bitswith equal values in the first N coefficients and in the last Ncoefficients in the coefficient sequence, and determining that awatermark is imbedded in the vicinity of the feature point of the imagewhen the number is less than a preset threshold, wherein the value of abit is calculated according to the parity of the bit, and the N is apositive integer.
 9. The method according to claim 8, furthercomprising: calculating a possibility of a bit of the coefficientsequence being odd or even, and calculating a bit credibility of a bitof the coefficient sequence when a watermark is imbedded; performing awatermark matching according to the bit credibility.
 10. The methodaccording to claim 9, wherein the step of calculating a possibility of abit of the coefficient sequence being odd or even, and calculating a bitcredibility of a bit of the coefficient sequence when a watermark isimbedded is: when a watermark is imbedded, counting a count Zero[i] ofan even ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculating a possibility of a bit ofthe coefficient sequence being odd based on a formula:oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1), and calculating apossibility of a bit of the coefficient sequence being even based on aformula: zeroProb[i]=ε^((2V−zero[i]))(1−ε)^(zero[i])(2), wherein ε is anaverage error rate on each bit, and i is a natural number; when there isa greater possibility of a bit of the coefficient sequence being odd,calculating the credibility as oneProb[i]/(oneProb[i]+zeroProb[i]); andwhen there is a greater possibility of a bit of the coefficient sequencebeing even, calculating the credibility aszeroProb[i]/(oneProb[i]+zeroProb[i]).
 11. The method according to claim9, wherein the performing a watermark matching according to the bitcredibility is: comparing the coefficient sequence with massivewatermark information in a database according to a descendingcredibility, and when an error occurs to the ith bit during thecomparison, returning to a resulted watermark that matches thecoefficient sequence on those bits from the 0th bit to the (i−1)th bit.12. A device for localized blind watermark detection, comprising: anextracting and transforming unit configured to extract a feature pointof an image, and perform domain transformation; and a watermark checkingunit configured to extract a sequence of a transformation domain of thevicinity of the feature point of the image, check the sequence bit bybit, and determine that a watermark is imbedded in the vicinity of thefeature point of the image when a number of bits with equal values inthe first N coefficients and in the last N coefficients in the sequenceis within a preset range.
 13. The device according to claim 12, whereinthe watermark checking unit is configured to: extract a coefficientsequence made up of multiple coefficients of a sub-block DCT of thevicinity of the feature point of the image, count the number of bitswith equal values in the first N coefficients and in the last Ncoefficients in the coefficient sequence, and determine that a watermarkis imbedded in the vicinity of the feature point of the image when thenumber is within a preset range, wherein the value of a bit iscalculated according to the parity of the bit, and the N is a positiveinteger.
 14. The device according to claim 12, further comprising: acredibility calculating unit configured to calculate a possibility of abit of the coefficient sequence being odd or even, and calculate a bitcredibility of a bit of the coefficient sequence when a watermark isimbedded; and a watermark matching unit configured to perform awatermark matching according to the bit credibility.
 15. The deviceaccording to claim 14, wherein the credibility calculating unit isconfigured to: when a watermark is imbedded, count a count Zero[i] of aneven ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculate a possibility of a bit of thecoefficient sequence being odd based on a formula:oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1), and calculate apossibility of a bit of the coefficient sequence being even based on aformula: zeroProb[i]=ε^((2V−zero[i]))(1−ε)^(zero[i]) (2), wherein ε isan average error rate on each bit, i is a natural number; when there isa greater possibility of a bit of the coefficient sequence being odd,calculate the credibility as oneProb[i]/(oneProb[i]+zeroProb[i]); andwhen there is a greater possibility of a bit of the coefficient sequencebeing even, calculate the credibility aszeroProb[i]/(oneProb[i]+zeroProb[i]).
 16. The device according to claim14, wherein the watermark matching unit is configured to: compare thecoefficient sequence with massive watermark information in a databaseaccording to a descending credibility, and when an error occurs to theith bit during the comparison, return to a resulted watermark thatmatches the coefficient sequence on those bits from the 0th bit to the(i−1)th bit.
 17. The device according to claim 13, further comprising: acredibility calculating unit configured to calculate a possibility of abit of the coefficient sequence being odd or even, and calculate a bitcredibility of a bit of the coefficient sequence when a watermark isimbedded; and a watermark matching unit configured to perform awatermark matching according to the bit credibility.
 18. The deviceaccording to claim 17, wherein the credibility calculating unit isconfigured to: when a watermark is imbedded, count a count Zero[i] of aneven ith bit and an odd (i+N)th bit in the coefficient sequencecorresponding to the watermark, calculate a possibility of a bit of thecoefficient sequence being odd based on a formula:oneProb[i]=(1−ε)^((2V−zero[i]))ε^(zero[i]) (1), and calculate apossibility of a bit of the coefficient sequence being even based on aformula: zeroProb[i]=ε^((2V−zero[i])) (1−ε)^(zero[i]) (2), wherein ε isan average error rate on each bit, i is a natural number; when there isa greater possibility of a bit of the coefficient sequence being odd,calculate the credibility as oneProb[i]/(oneProb[i]+zeroProb[i]); andwhen there is a greater possibility of a bit of the coefficient sequencebeing even, calculate the credibility aszeroProb[i]/(oneProb[i]+zeroProb[i]).
 19. The device according to claim17, wherein the watermark matching unit is configured to: compare thecoefficient sequence with massive watermark information in a databaseaccording to a descending credibility, and when an error occurs to theith bit during the comparison, return to a resulted watermark thatmatches the coefficient sequence on those bits from the 0th bit to the(i−1)th bit.